Facility Location Modeling And Optimization Algorithm

Location problem is one of the classic operations research, The traditional objective of location is the pursuit of cost minimization, That is the single objective optimization. However, many real world location problems are related to the multiple targets while optimizing, Multi-objective optimization has developed a new discipline in the last 30 years. Over the years many researchers are looking for some techniques to treat multi-objective optimization problems. The emergence of evolutionary algorithms provides a new way to solve complex optimization problems, because of its intelligence, versatility, robustness, arallelism and global search capability, It has been widely successful application In various fields.This paper first introduces the emergence, development of location problem and its Research objectives, research significance. Then based on the application of Multi-objective evolutionary algorithm in facility location Problem, made the following two aspects of work:(1) On the basis of analyzing existing literature, this paper sets the time to customer satisfaction as a measurement of logistics distribution center location, proposes the method of calculating the time to customer satisfaction, establishes the multi-objective optimization model with the goal of minimizing the logistics cost and maximizing customers'satisfaction. In this paper a multi-objective evolutionary algorithm based on NSGA-â…¡is specialized to solve the problem. By selecting the appropriate encoding method and genetic operators,can get the optimal solutions to the model, a practical example shows the validity of the model and algrithm. this model can get several efficient solutions in one generation, so it provides a more comprehensive decision support for decision-makers.(2) According to the characteristics of urban life waste collection and transportaion sys-tem, this paper establish a multi-objective model of solid waste transfer station site selection based on a reverse flow network. It considered the minimum total cost, the minimum total distance of Pitch corresponding to the garbage collection transfer station and maximized the minimum distance from residential areas to waste disposal center. In this paper a multi-objective evolutionary algorithn based on SPEA2 is specialized to solve the problem, by selecting the appropriate encoding method and genetic operators, can get the optimal solutions to the model, a practical example shows the validity of the model and algorithm, this model can get several efficient solutions in one generation, so it provides a more comprehensive decision support for decision-makers.